Fuzzy And Neural Approaches in Engineering / Edition 1

Fuzzy And Neural Approaches in Engineering / Edition 1

ISBN-10:
0471160032
ISBN-13:
9780471160038
Pub. Date:
02/05/1997
Publisher:
Wiley
ISBN-10:
0471160032
ISBN-13:
9780471160038
Pub. Date:
02/05/1997
Publisher:
Wiley
Fuzzy And Neural Approaches in Engineering / Edition 1

Fuzzy And Neural Approaches in Engineering / Edition 1

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Overview

Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. This definitive book presents the fundamentals of both technologies, and demonstrates how to combine the unique capabilities of these two technologies for the greatest advantage. Steering clear of unnecessary mathematics, the book highlights a wide range of dynamic possibilities and offers numerous examples to illuminate key concepts. It also explores the value of relating genetic algorithms and expert systems to fuzzy and neural technologies.

Product Details

ISBN-13: 9780471160038
Publisher: Wiley
Publication date: 02/05/1997
Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control , #10
Pages: 600
Product dimensions: 6.30(w) x 9.43(h) x 1.46(d)

About the Author

LEFTERI H. TSOUKALAS, PhD, is on the faculty of the School of Nuclear Engineering at Purdue University and is an active industrial consultant and speaker. ROBERT E. UHRIG, PhD, holds a joint appointment as Distinguished Professor in the Nuclear Engineering Department at the University of Tennessee and Distinguished Scientist in the Instrumentation and Control Division at the Oak Ridge National Laboratory. He is the author of Random Noise Techniques in Nuclear Reactor Systems.

Table of Contents

Introduction to Hybrid Artificial Intelligence Systems.

FUZZY SYSTEMS: CONCEPTS AND FUNDAMENTALS.

Foundations of Fuzzy Approaches.

Fuzzy Relations.

Fuzzy Numbers.

Linguistic Descriptions and Their Analytical Forms.

Fuzzy Control.

NEURAL NETWORKS: CONCEPTS AND FUNDAMENTALS.

Fundamentals of Neural Networks.

Backpropagation and Related Training Algorithms.

Competitive, Associative, and Other Special Neural Networks.

Dynamic Systems and Neural Control.

Practical Aspects of Using Neural Networks.

INTEGRATED NEURAL-FUZZY TECHNOLOGY.

Fuzzy Methods in Neural Networks.

Fuzzy Methods in Fuzzy Systems.

Selected Hybrid Neurofuzzy Applications.

Dynamic Hybrid Neurofuzzy Systems.

OTHER ARTIFICAL INTELLIGENCE SYSTEMS.

Expert Systems in Neurofuzzy Systems.

Genetic Algorithms.

Epilogue.

Appendix.

Index.
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